Evidence map›Paper›PMID 36651735›Full record

ArticlemBio2023

Microbiome Features Differentiating Unsupervised-Stratification-Based Clusters of Patients with Abnormal Glycometabolism.

Ting Xu, Xuejiao Wang, Yu Chen, Hui Li, Liping Zhao, Xiaoying Ding, Chenhong Zhang

Open access · goldAbstract read
In one paragraph

Article in mBio, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 10 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Ting Xu *State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Xuejiao Wang *Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yu ChenState Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Hui LiState Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Liping ZhaoState Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.
Xiaoying DingDepartment of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Chenhong ZhangState Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-4462-892X
Shanghai Jiao Tong University · CNRutgers, The State University of New Jersey · US

Funding

Translational Research Support CoreP30ES005022 · NIEHS · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI ROBERT John LAUMBACH · 1988 to 2026
$47.4M
NIEHS NIH HHS P30 ES005022
6 · The paper itself

Abstract

The alteration of gut microbiota structure plays a pivotal role in the pathogenesis of abnormal glycometabolism. However, the microbiome features identified in patient groups stratified solely based on glucose levels remain controversial among different studies. In this study, we stratified 258 participants (discovery cohort) into three clusters according to an unsupervised method based on 16 clinical parameters involving the levels of blood glucose, insulin, and lipid. We found 67 cluster-specific microbiome features (i.e., amplicon sequence variants [ASVs]) based on 16S rRNA gene V3-V4 region sequencing. Specifically, ASVs belonging to

Indexed as

Diabetes Mellitus, Type 2Insulin ResistanceMicrobiotaBacteriaBlood GlucoseCholesterolHumansInsulinRNA, Ribosomal, 16SBlood GlucoseCholesterolInsulinRNA, Ribosomal, 16Sglycometabolisminsulin resistancemicrobiome featuresunsupervised stratification

Identifiers

PMID36651735
PMCPMC9973283
OpenAlexW4317213613

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.